Selectivity prediction for frog-type peptide antibiotics against Gram-negative bacteria (CROSBI ID 557401)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa
Podaci o odgovornosti
Juretić, Davor
engleski
Selectivity prediction for frog-type peptide antibiotics against Gram-negative bacteria
We have developed the D-descriptor model for predicting the therapeutic index (TI) of frog-derived antimicrobial peptides (AMPs). It is linear one-parameter model which produces high correlation among predicted and measured TI (r2=0.83) for almost forty non-homologous AMPs. The single parameter used is cosine of the angle between two sequence moments for given peptide sequence bent in the π/2 arc. In the case of pseudin 2 measured and predicted TI are 6 and 7 (for separation angle of 15 degrees between sequence moments) respectively, but single point mutation (N3K) has dramatic effect in increasing TI to measured and predicted value of 34 and 36 (for separation angle of 72 degrees between sequence moments) respectively. We shall discuss sequence moments definition and relevance of this research for finding novel antibiotics with little likelihood to elicit bacterial resistance development.
peptide antibiotics; selectivity prediction
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Podaci o prilogu
40-40.
2009.
objavljeno
Podaci o matičnoj publikaciji
The 3rd Adriatic Meeting on Computational Solutions in the Life Sciences
Tomić, Sanja ; Smith, David
Zagreb: Centre for Computational Solutions in the Life Sciences, Ruđer Bošković Institute
978-953-6690-80-0
Podaci o skupu
The 3^rd Adriatic Meeting on Computational Solutions in the Life Sciences
pozvano predavanje
01.09.2009-05.09.2009
Primošten, Hrvatska